![]() If you experience any problems that you cannot solve yourself, consider checking out the official Ejabberd (XMPP) chat room at: case you need an example configuration for inspiration, check out Updating Ejabberdīefore updating Ejabberd, make sure you’ve carefully read the release notes for the corresponding version on the ProcessOne blog! The log file in /var/log/ejabberd/ejabberd.log should give you valuable information on the startup of Ejabberd. ![]() We’re installing it to be able to control the XMPP server via Systemd: cp rvice /etc/systemd/system/Īs soon as your server is configured in /etc/ejabberd/ejabberd.yml, start your server using systemctl start ejabberd The make process did also create a Systemd service file. To install all the files at the right location. Before to that, a new System user for ejabberd is created: adduser -system -group -home /var/lib/ejabberd ejabberd It is now time to install Ejabberd on the system. The build process will take some time, but soon you should be presented a terminal windows with no error messages in it. configure -help will show you all the available configuration flags that might be interesting for your environment./autogen.sh I’m enabling the PostgreSQL support here. Then install the build dependencies: apt updateĭownload the Ejabberd source code to your home directory and select the latest version (at the time of writing: 20.04): git clone git:///processone/ejabberd.git ejabberdĬonfiguring and running the build process Instructions for activating the Backports can be found here: You will need Debian’s official “Buster Backports” repository for some erlang dependencies that we’re going to install. The compile process will vary a little bit if you’re utilizing Ejabberd’s Mnesia DB or MySQL. By the way: I’m using Ejabberd with PostgreSQL as a backend. I’m able to use the latest patches / updates on GitHubĪs soon as the build time package dependencies are clear, the build process it pretty straight forward.Ejabberd can be updated independently from any Debian packaging processes / workflows.That would give me the following benefits: The Debian project’s Ejabberd maintainer was not sure about the final release date of Ejabberd 20.04 in the Backports repo, so I chose for compiling Ejabberd myself to get my hands on the latest version as soon as possible. While the repo was stuck at 20.02, I wanted to provide the users 20.04 to be able to drastically improve the user experience during video calls. This was done mainly because the “Debian Backports” repository did not offer the version of Ejabberd that I urgently needed. is a shortly-to-be-published blog post giving more context, fwiw.Lately I switched from a binary Ejabberd package to a self-built version of Ejabberd on my XMPP server. Historically, joining rooms in Matrix was O(N) with the number of the users in that room, but we’ve recently fixed this with “faster remote joins”, which allows the room state to get lazily synced in the background, thus making it O(1) with size of room, as it should be. And to be clear, Matrix never scales with the amount of history in a room history is always lazyloaded so it doesn’t matter how much scrollback there is. ![]() In practice, you can definitely write a Matrix implementation where all operations (joining, sending, receiving, etc) are O(1) per destination, and don’t scale with the amount of state (i.e. It’s like pointing out that writing an efficient Git implementation is harder than writing an efficient CVS implementation hardly surprising given the difference in semantics. Matrix is certainly more complex to scale (as our inefficient first gen implementations demonstrated), but i think folks are conflating together “it’s complex to write an efficient implementation” with “it doesn’t scale”. We’ve pinged them on Twitter to see if they want to discuss what they’re up to :) It would be really cool if Process One is doing something like that with ejabberd, but in practice we suspect that they’ve just done an efficiently implementation of the current state res algorithm. and give a bit of an idea of how that works. all key-value pairs of data associated with the room) en masse. There’s an interesting optimisation that we designed back in 2018 where you incrementally resolve state (so called ‘delta state res’), where you only resolve the state which has changed rather than considering all the room state (i.e. The Dendrite go implementation is pretty fast too. The Synapse python implementation was historically terrible at this, but has been optimised a lot in the last 12 months. Generally this is trivial, but if there’s a merge conflict, it’s heavier to resolve. It’s true that every time you send a message in matrix you effectively are merging the state of one chatroom with the state of another one - very similar to how you push a commit in Git. We’d like to know too :) Matrix as protocol isn’t inherently unscalable at all.
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